Alignment by Maximization of Mutual Information
International Journal of Computer Vision
2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications
2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications
A generalized divergence measure for robust image registration
IEEE Transactions on Signal Processing
Multimodality image alignment using information-theoretic approach
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
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We present an image registration approach by optimizing an information divergence based on the nonextensive Tsallis entopy. The optimization is carried out using a modified simultaneous perturbation stochastic approximation algorithm. And we show that this entropic divergence attains its maximum value when the conditional intensity probabilities between the reference image and the transformed target image are degenerate distributions. Experimental results are provided to demonstrate the registration accuracy of the proposed technique in comparison to existing entropic image alignment approaches.